An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer
| Autor: | Zuwairie Ibrahim, Saifudin Razali, Mohd Ibrahim Shapiai, Asrul Adam, Nor Hidayati Abdul Aziz, Nor Azlina Ab Aziz, Mohd Falfazli Mat Jusof |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
education.field_of_study
Mathematical optimization Optimization problem Optimization algorithm Simulated kalman filter 020208 electrical & electronic engineering Population Process (computing) Large population 02 engineering and technology Kalman filter 03 medical and health sciences 0302 clinical medicine 030220 oncology & carcinogenesis 0202 electrical engineering electronic engineering information engineering education |
| Zdroj: | 2018 8th International Conference on Intelligent Systems, Modelling and Simulation (ISMS). |
| DOI: | 10.1109/isms.2018.00013 |
| Popis: | This paper presents an analysis of simulated Kalman filter (SKF) optimization algorithm. The SKF algorithm is a population-based optimization algorithm and thus, requires the use of agents to perform a search process. In optimization, usually, different number of agent produces different performance in solving optimization problems. In this paper, the performance of SKF is investigated using different number of agent, from 10 up to 1000 agents. Using the same number of fitness evaluations, experimental results indicate that a surprisingly large population size offers higher performance in solving most optimization problems. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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